MétaCan
Menu
Back to cohort
Record W2988855473 · doi:10.1016/j.jhepr.2019.10.005

Efficacy of rituximab in difficult-to-manage autoimmune hepatitis: Results from the International Autoimmune Hepatitis Group

2019· article· en· W2988855473 on OpenAlexaffabout
Nwe Ni Than, James Hodson, Daniel Schmidt-Martin, Richard Taubert, Rebecca E. Wawman, Meemee Botter, K Böck, Rebecca Jones, Gautham Appanna, Andrew Godkin, Aldo J. Montaño‐Loza, Frank Lammert, Christoph Schramm, Michael P. Manns, Mark G. Swain, Kelly W. Burak, David Adams, Gideon M. Hirschfield, Ye Htun Oo

Bibliographic record

VenueJHEP Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsUniversity of TorontoUniversity Health NetworkUniversity of CalgaryUniversity of Alberta
FundersSir Jules Thorn Charitable TrustMedical Research CouncilNational Institute for Health and Care Research
KeywordsAutoimmune hepatitisMedicineRituximabPrednisoloneInternal medicineHepatitisRetrospective cohort studyCohortAdverse effectGastroenterologyImmunologyPediatricsLymphoma

Abstract

fetched live from OpenAlex

Background & Aims Treatment options remain limited for patients with autoimmune hepatitis (AIH), while there are still concerns over the consequences of long-term corticosteroid use. A few studies have suggested a role for B cell-driven autoimmune liver injury in AIH. This multicentre, international retrospective cohort study from the International Autoimmune Hepatitis Group aims to evaluate the clinical efficacy and safety of rituximab in difficult-to-manage AIH. Methods Clinical data from 22 patients who received rituximab between 2007 and 2017 were collected from centres in the United Kingdom, Germany and Canada. Clinical response was assessed using changes in biochemical and immunological parameters up to 24 months post-rituximab infusion. In addition, we compared the doses of prednisolone used 3 months before and 12 months after treatment, and assessed freedom from AIH flares over the post-treatment period. Results Twenty-two patients with type-1 AIH were included, with a median age of 40 years at diagnosis (range 19–79); 15/22 (68%) were female and 18/22 (82%) were Caucasian. The median period from diagnosis to the end of follow-up in these patients was 11 years (range 3–28). Values of alanine aminotransferase, aspartate aminotransferase and albumin improved significantly following rituximab therapy, and were sustained for up to 2 years (all p ≪0.001). Prednisolone doses were significantly reduced by 12 months post-treatment ( p = 0.003), with 13/21 (62%) patients having a dose reduction. Over a median post-treatment follow-up period of 6 years (range 1–10), 5 patients developed AIH flares at a median of 22 months post-treatment, giving an estimated 71% freedom from AIH flare at 2 years. Four of these patients received a second course of treatment, of whom 2 had subsequent further flares. No serious adverse events attributable to rituximab were recorded. Conclusion In patients with difficult-to-manage AIH, rituximab appears to be clinically effective and well tolerated. Rituximab was associated with sustained improvements in serum liver tests, an absence of clinical disease flares, and a reduction in prednisolone dose. Controlled trials are warranted to further evaluate B cell-targeting therapies in patients with AIH. Lay summary Autoimmune hepatitis is an autoimmune condition of the liver, usually treated with medications that suppress the immune system, such as steroids. However, some patients do not respond to this treatment. We analysed the safety and efficacy of rituximab in patients who were not responding to first- or second-line therapies. Rituximab was safe and improved liver blood tests in 70% of patients over a 2-year follow-up period, while enabling steroid doses to be reduced in two-thirds of patients, which is a very positive clinical outcome.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.241
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations99
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueJHEP ReportsSame topicLiver Diseases and ImmunityFrench-language works237,207